Integration of Center and Integration of Center and Eastern European Stock Eastern European Stock
MarketsMarkets
MSc student IOSIF ANAIDA
Coordinator Professor Moisă Altăr
The Academy of Economic Studies
Doctoral School of Finance and Banking
Bucharest, July 2007
Dissertation paper outline
The integration of the emerging stock markets
The aims of the paper
Empirical studies concerning stock markets integration
The Data
Testing the cointegration
Testing the correlation
Conclusions
References
DifferentDifferent approachesapproaches
Bekaert and Harvey (1997) – market liberalization increase the correlation between local market returns and the world market but do not drive up local volatility .
Forbs and Rigobon (1999) – there was no contagion during the euro-Asia crises in 1997, the Mexican peso collapse in 1994 and in the US stock market crash in 1987. High market co-movements during these periods where a continuation of strong cross-market linkages
Egert and Kocenda (2005) – there are no robust cointegration relationship between emerging and developed markets. But there are short-term spillover effects in terms of stock returns and stock price volatility.
Cappielo, G’erard, Kadareja and Manganelli (2006) – larger new EU member state exhibit a strong comovements between themselves and with the euro area. Form the smaller countries only Estonia and Cyprus show integration bough with the euro zone and the block of large economies.
The DataThe Data
0
1000
2000
3000
4000
5000
2001 2002 2003 2004 2005 2006
ATX
4000
8000
12000
16000
20000
24000
28000
2001 2002 2003 2004 2005 2006
BUX
200
400
600
800
1000
1200
1400
1600
1800
2001 2002 2003 2004 2005 2006
PX
0
200
400
600
800
1000
1200
1400
1600
2001 2002 2003 2004 2005 2006
SOFIX
800
1200
1600
2000
2400
2800
3200
3600
2001 2002 2003 2004 2005 2006
WIG
0
2000
4000
6000
8000
10000
2001 2002 2003 2004 2005 2006
BET
Initial data series: Initial data series:
Bucharest Exchange Bucharest Exchange Trading index (BETTrading index (BET), ),
Prague Exchange index Prague Exchange index (PX), (PX),
Warsaw Exchange index Warsaw Exchange index (WIG20),(WIG20),
Bulgarian Exchange index Bulgarian Exchange index (SOFIX),(SOFIX),
Budapest Stock Index Budapest Stock Index (BUX)(BUX)
Austrian Traded Index Austrian Traded Index (ATX). (ATX).
Time length: Time length: 20.10.2000 – 04.03.200720.10.2000 – 04.03.2007
The Cointegration analThe Cointegration analysesses
Verify stationarity of series using ADT, Phillips-Perron and KPSS tests: the series are not stationary in level but is stationary in first difference Check the cointegration relationship between the variables using the Engle Granger residual based cointegration method:
Estimate residuals series for each regression. Verify the stationarity of the residual series using ADF and PP tests. Comparing the test statistic with the critical values estimated by Engle and Yoo.
Engle-Granger cointegration test
Variables ADF PP
ATX -3.420593* -3.509189*
BET -3.648032* -3.380750*
BUX -4.589758* -4.270524*
PX -5.088.152 -4.560678*
WIG -3.674414* -3.486132*
SOFIX -2.972781* -3.215374*
n
i ttiit YX1 ,1
Cointegration analysis
Johansen method in a VAR framework Select numbers of lags to include in the VAR using the Akaike informational criterion Check VAR stability
tktkttktt yyyyy )1(12211 ...
Cointegration - conclusions
The residuals are not stationary, the value of t statistic is higher then the critical value The Johansen method – the teststatistic is smaller then the critical values There is no cointegration relationship between the series.
No. of cointegration
Eigenvalue Test statistic 5% critical value
1% critical value
None 0.020503 29.99762 39.37 45.10At most 1 0.011279 16.42501 33.46 38.77At most 2 0.010257 14.92850 27.07 32.24At most 3 0.007897 11.48052 20.97 25.52At most 4 0.004609 6.688568 14.07 18.63At most 5 3.56E-05 0.051499 3.76 6.65
Johansen cointegration test-eigenvalue max
No.of cointegration
Eigenvalue Test statistic 5% critical value
1% critical value
None 0.020503 79.57171 94.15 103.18At most 1 0.011279 49.57410 68.52 76.07At most 2 0.010257 33.14909 47.21 54.46At most 3 0.007897 18.22059 29.68 35.65At most 4 0.004609 6.740067 15.41 20.04At most 5 3.56E-05 0.051499 3.76 6.65
Johansen cointegration test-eigenvalue trace
The correlation analysis for the returns
Calculating the returns: dl_indexCalculating the returns: dl_index
ATX BET BUX PX SOFIX WIGATX 1.000000 0.037999 0.445384 0.487496 -0.014321 0.375169BET 0.037999 1.000000 0.016596 -0.021922 0.016283 0.017652BUX 0.445384 0.016596 1.000000 0.545900 0.027081 0.536316PX 0.487496 -0.021922 0.545900 1.000000 0.044288 0.497050SOFIX -0.014321 0.016283 0.027081 0.044288 1.000000 -0.003174WIG 0.375169 0.017652 0.536316 0.497050 -0.003174 1.000000
Correlation matrix for returnsCorrelation matrix for returns
The correlation analysis
Choosing the order of the variables using the F-test, market capitalization Choosing the order of the variables using the F-test, market capitalization and the efficiency of the market: ATX, WIG, PX, BUX, BET, SOFIX. and the efficiency of the market: ATX, WIG, PX, BUX, BET, SOFIX. Verify the sign and proportion of the spillover between the returns using Verify the sign and proportion of the spillover between the returns using the impulse response and variance decomposition. the impulse response and variance decomposition.
k
i
k
i ttitit XYY1 1 111
k
i
k
i ttitit YXX1 1 111
ATX WIG BUX PX BET SOFIXATX - 0.8864 0.7603 0.0710 0.9771 0.3061WIG 0.5379 - 0.3632 0.7832 0.7919 0.8956BUX 0.0954 0.4349 - 0.7776 0.8995 0.8116PX 0.6382 0.5534 0.5316 - 0.1943 0.3178BET 0.6461 0.0311 0.8891 0.2188 - 0.5890SOFIX 0.3594 0.2729 0.1126 0.8735 0.4195 -
Granger causality test for returnsDependent variable
Lags of variable
Lag length criteria suggests a specification including 1 lagLag length criteria suggests a specification including 1 lag
Verify the short-term interaction between returns using Granger causality test:Verify the short-term interaction between returns using Granger causality test:
The response of returns to shocks applied on the other marketsThe response of returns to shocks applied on the other markets
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_ATX to D_ATX
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_ATX to D_WIG
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_ATX to D_BUX
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_ATX to D_PX
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_ATX to D_BET
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_ATX to D_SOFIX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_WIG to D_ATX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_WIG to D_WIG
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_WIG to D_BUX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_WIG to D_PX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_WIG to D_BET
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_WIG to D_SOFIX
.000
.004
.008
.012
1 2 3
Response of D_BUX to D_ATX
.000
.004
.008
.012
1 2 3
Response of D_BUX to D_WIG
.000
.004
.008
.012
1 2 3
Response of D_BUX to D_BUX
.000
.004
.008
.012
1 2 3
Response of D_BUX to D_PX
.000
.004
.008
.012
1 2 3
Response of D_BUX to D_BET
.000
.004
.008
.012
1 2 3
Response of D_BUX to D_SOFIX
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_PX to D_ATX
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_PX to D_WIG
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_PX to D_BUX
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_PX to D_PX
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_PX to D_BET
-.002
.000
.002
.004
.006
.008
.010
.012
1 2 3
Response of D_PX to D_SOFIX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_BET to D_ATX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_BET to D_WIG
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_BET to D_BUX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_BET to D_PX
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_BET to D_BET
-.004
.000
.004
.008
.012
.016
1 2 3
Response of D_BET to D_SOFIX
-.004
.000
.004
.008
.012
.016
.020
.024
1 2 3
Response of D_SOFIX to D_ATX
-.004
.000
.004
.008
.012
.016
.020
.024
1 2 3
Response of D_SOFIX to D_WIG
-.004
.000
.004
.008
.012
.016
.020
.024
1 2 3
Response of D_SOFIX to D_BUX
-.004
.000
.004
.008
.012
.016
.020
.024
1 2 3
Response of D_SOFIX to D_PX
-.004
.000
.004
.008
.012
.016
.020
.024
1 2 3
Response of D_SOFIX to D_BET
-.004
.000
.004
.008
.012
.016
.020
.024
1 2 3
Response of D_SOFIX to D_SOFIX
Response to Cholesky One S.D. Innovations ± 2 S.E.
Variance decomposition for the returnsVariance decomposition for the returns
The initial shock in the returns The initial shock in the returns works through the system in about 3 works through the system in about 3 daysdays None of the emergent markets None of the emergent markets influence the Austrian returns, but influence the Austrian returns, but changes in returns on the three changes in returns on the three larger emergent stock markets are larger emergent stock markets are due to changes in the Austrian due to changes in the Austrian returnsreturnsThe three larger emergent The three larger emergent markets: Poland, Czech Republic markets: Poland, Czech Republic and Hungary are correlated between and Hungary are correlated between themselves in terms of returns themselves in terms of returns BET and SOFIX returns seem BET and SOFIX returns seem uninfluenced by the movements of uninfluenced by the movements of the other returns.the other returns.
Days ahead D_ATX D_WIG D_PX D_BUX D_BET D_SOFIX1 100.0000 0.000000 0.000000 0.000000 0.000000 0.0000002 99.59105 0.044013 0.286347 0.007451 3.33E-06 0.0711393 99.58768 0.044011 0.287208 0.007801 0.000799 0.072503
Days ahead D_ATX D_WIG D_PX D_BUX D_BET D_SOFIX1 14.17161 85.82839 0.000000 0.000000 0.000000 0.0000002 14.10401 85.81295 0.021019 0.056347 0.004508 0.0011683 14.10415 85.81132 0.021926 0.056702 0.004724 0.001177
Days ahead D_ATX D_WIG D_PX D_BUX D_BET D_SOFIX1 23.69439 11.67964 64.62597 0.000000 0.000000 0.0000002 23.59788 11.63133 64.56473 0.023212 0.115084 0.0677623 23.59706 11.63074 64.56074 0.023219 0.120464 0.067778
Days ahead D_ATX D_WIG D_PX D_BUX D_BET D_SOFIX1 19.80737 15.93645 5.813288 58.44290 0.000000 0.0000002 20.07214 15.91336 5.791510 58.21816 0.000972 0.0038623 20.07180 15.91375 5.792217 58.21720 0.001113 0.003918
Days ahead D_ATX D_WIG D_PX D_BUX D_BET D_SOFIX1 0.149843 0.007663 0.243116 0.016866 99.58251 0.0000002 0.156055 0.222483 0.295727 0.019366 99.28715 0.0192243 0.155925 0.237918 0.299797 0.019994 99.26612 0.020247
Days ahead D_ATX D_WIG D_PX D_BUX D_BET D_SOFIX1 0.020217 0.001275 0.311388 0.063885 0.043412 99.559822 0.042319 0.011096 0.330570 0.218532 0.092179 99.305303 0.044023 0.011096 0.330957 0.219286 0.092734 99.30190
Variance decomposition for SOFIX returns
Variance decomposition for BUX returns
Variance decomposition for PX returns
Variance decomposition for ATX returns
Variance decomposition for WIG returns
Variance decomposition for BET returns
Methods in obtaining returns volatility
Obtained variances series for returns using GARCH(1,1) methodObtained variances series for returns using GARCH(1,1) method - the mean equation:- the mean equation:
ttt yy 1
21
21
2 ttt
- the conditional variance equation:- the conditional variance equation:
Using a EGARCH(1,1,1) method to estimate variance for SOFIX returnsUsing a EGARCH(1,1,1) method to estimate variance for SOFIX returns Conditional variance equation for the EGARCH:Conditional variance equation for the EGARCH:
2
)ln()ln(2
1
1
21
121
2
t
t
t
ttt
Advantages in using a EGARCH method: Advantages in using a EGARCH method: - the coefficients can be negative because - the coefficients can be negative because )ln( 2
t is modeled.is modeled.- the asymmetry of the EGARCH model capture the leverage effect. - the asymmetry of the EGARCH model capture the leverage effect.
Volatility - the correlation analyzeVolatility - the correlation analyze
Verify stationarity of the variance using the ADF and PP tests, the series Verify stationarity of the variance using the ADF and PP tests, the series are stationary at any significance level. are stationary at any significance level. Check the relation between the series using the matrix correlation and GrangerCheck the relation between the series using the matrix correlation and GrangerCausality test. Causality test.
ATX BET BUX SOFIX PX WIGATX - 0.6707 0.4989 0.1782 0.8455 0.8701
BET 0.5589 - 0.0259 0.3360 0.1367 0.0946
BUX 0.3143 0.6825 - 0.2474 0.0401 0.3882SOFIX 0.7626 0.9919 0.3906 - 0.9509 0.0285
PX 0.1647 0.9934 0.1262 0.1319 - 0.8961
WIG 0.7174 0.9941 0.2192 0.3314 0.4108 -
Granger causality test for varianceDependent variable
Lags of variable
ATX BET BUX PX SOFIX WIGATX 1.000000 -0.075787 0.461381 0.522018 -0.046720 0.179787
BET -0.075787 1.000000 0.062745 -0.035368 -0.033744 -0.166919
BUX 0.461381 0.062745 1.000000 0.675333 0.038740 0.332519
PX 0.522018 -0.035368 0.675333 1.000000 0.106245 0.347898
SOFIX -0.046720 -0.033744 0.038740 0.106245 1.000000 0.366838
WIG 0.179787 -0.166919 0.332519 0.347898 0.366838 1.000000
Correlation matrix for volatiles
Impulse response for volatility Impulse response for volatility
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
.00006
25 50 75 100 125 150 175 200
Response of D_ATXVARIANCE to D_ATXVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
.00006
25 50 75 100 125 150 175 200
Response of D_ATXVARIANCE to D_WIGVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
.00006
25 50 75 100 125 150 175 200
Response of D_ATXVARIANCE to D_BUXVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
.00006
25 50 75 100 125 150 175 200
Response of D_ATXVARIANCE to D_PXVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
.00006
25 50 75 100 125 150 175 200
Response of D_ATXVARIANCE to D_BETVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
.00006
25 50 75 100 125 150 175 200
Response of D_ATXVARIANCE to D_SOFIXVARIANCE
-.000008
-.000004
.000000
.000004
.000008
.000012
.000016
25 50 75 100 125 150 175 200
Response of D_WIGVARIANCE to D_ATXVARIANCE
-.000008
-.000004
.000000
.000004
.000008
.000012
.000016
25 50 75 100 125 150 175 200
Response of D_WIGVARIANCE to D_WIGVARIANCE
-.000008
-.000004
.000000
.000004
.000008
.000012
.000016
25 50 75 100 125 150 175 200
Response of D_WIGVARIANCE to D_BUXVARIANCE
-.000008
-.000004
.000000
.000004
.000008
.000012
.000016
25 50 75 100 125 150 175 200
Response of D_WIGVARIANCE to D_PXVARIANCE
-.000008
-.000004
.000000
.000004
.000008
.000012
.000016
25 50 75 100 125 150 175 200
Response of D_WIGVARIANCE to D_BETVARIANCE
-.000008
-.000004
.000000
.000004
.000008
.000012
.000016
25 50 75 100 125 150 175 200
Response of D_WIGVARIANCE to D_SOFIXVARIANCE
-.000005
.000000
.000005
.000010
.000015
.000020
.000025
25 50 75 100 125 150 175 200
Response of D_BUXVARIANCE to D_ATXVARIANCE
-.000005
.000000
.000005
.000010
.000015
.000020
.000025
25 50 75 100 125 150 175 200
Response of D_BUXVARIANCE to D_WIGVARIANCE
-.000005
.000000
.000005
.000010
.000015
.000020
.000025
25 50 75 100 125 150 175 200
Response of D_BUXVARIANCE to D_BUXVARIANCE
-.000005
.000000
.000005
.000010
.000015
.000020
.000025
25 50 75 100 125 150 175 200
Response of D_BUXVARIANCE to D_PXVARIANCE
-.000005
.000000
.000005
.000010
.000015
.000020
.000025
25 50 75 100 125 150 175 200
Response of D_BUXVARIANCE to D_BETVARIANCE
-.000005
.000000
.000005
.000010
.000015
.000020
.000025
25 50 75 100 125 150 175 200
Response of D_BUXVARIANCE to D_SOFIXVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
25 50 75 100 125 150 175 200
Response of D_PXVARIANCE to D_ATXVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
25 50 75 100 125 150 175 200
Response of D_PXVARIANCE to D_WIGVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
25 50 75 100 125 150 175 200
Response of D_PXVARIANCE to D_BUXVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
25 50 75 100 125 150 175 200
Response of D_PXVARIANCE to D_PXVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
25 50 75 100 125 150 175 200
Response of D_PXVARIANCE to D_BETVARIANCE
-.00001
.00000
.00001
.00002
.00003
.00004
.00005
25 50 75 100 125 150 175 200
Response of D_PXVARIANCE to D_SOFIXVARIANCE
-.00002
.00000
.00002
.00004
.00006
.00008
.00010
.00012
25 50 75 100 125 150 175 200
Response of D_BETVARIANCE to D_ATXVARIANCE
-.00002
.00000
.00002
.00004
.00006
.00008
.00010
.00012
25 50 75 100 125 150 175 200
Response of D_BETVARIANCE to D_WIGVARIANCE
-.00002
.00000
.00002
.00004
.00006
.00008
.00010
.00012
25 50 75 100 125 150 175 200
Response of D_BETVARIANCE to D_BUXVARIANCE
-.00002
.00000
.00002
.00004
.00006
.00008
.00010
.00012
25 50 75 100 125 150 175 200
Response of D_BETVARIANCE to D_PXVARIANCE
-.00002
.00000
.00002
.00004
.00006
.00008
.00010
.00012
25 50 75 100 125 150 175 200
Response of D_BETVARIANCE to D_BETVARIANCE
-.00002
.00000
.00002
.00004
.00006
.00008
.00010
.00012
25 50 75 100 125 150 175 200
Response of D_BETVARIANCE to D_SOFIXVARIANCE
-.00005
.00000
.00005
.00010
.00015
.00020
.00025
.00030
25 50 75 100 125 150 175 200
Response of D_SOFIXVARIANCE to D_ATXVARIANCE
-.00005
.00000
.00005
.00010
.00015
.00020
.00025
.00030
25 50 75 100 125 150 175 200
Response of D_SOFIXVARIANCE to D_WIGVARIANCE
-.00005
.00000
.00005
.00010
.00015
.00020
.00025
.00030
25 50 75 100 125 150 175 200
Response of D_SOFIXVARIANCE to D_BUXVARIANCE
-.00005
.00000
.00005
.00010
.00015
.00020
.00025
.00030
25 50 75 100 125 150 175 200
Response of D_SOFIXVARIANCE to D_PXVARIANCE
-.00005
.00000
.00005
.00010
.00015
.00020
.00025
.00030
25 50 75 100 125 150 175 200
Response of D_SOFIXVARIANCE to D_BETVARIANCE
-.00005
.00000
.00005
.00010
.00015
.00020
.00025
.00030
25 50 75 100 125 150 175 200
Response of D_SOFIXVARIANCE to D_SOFIXVARIANCE
Response to Cholesky One S.D. Innovations ± 2 S.E.
Variance Decomposition for volatilityVariance Decomposition for volatility
The initial shock in the volatilities The initial shock in the volatilities works through the system in about works through the system in about 90 days, exception being WIG 90 days, exception being WIG volatility which affects the market for volatility which affects the market for about 5 months. about 5 months. Changes in ATX volatility have a Changes in ATX volatility have a positive influence on Poland, Czech positive influence on Poland, Czech Republic and Hungarian volatility. Republic and Hungarian volatility. The three larger emergent The three larger emergent markets are correlated in terms of markets are correlated in terms of volatilities between themselves.volatilities between themselves. Romanian and Bulgarian Romanian and Bulgarian volatilities are correlated with volatilities are correlated with volatilities in Poland and Hungary.volatilities in Poland and Hungary.
Period ATX WIG PX BUX BET SOFIX1 100.0000 0.000000 0.000000 0.000000 0.000000 0.000000
30 98.28603 0.164898 0.025445 0.425067 0.343396 0.75516390 98.21085 0.181920 0.041278 0.452319 0.344078 0.769553
Period ATX WIG PX BUX BET SOFIX1 6.809933 93.19007 0.000000 0.000000 0.000000 0.000000
30 1.005268 87.43912 0.337155 1.220722 0.014976 0.93534190 9.585778 86.66214 0.287021 2.076229 0.031225 1.357606
Period ATX WIG PX BUX BET SOFIX1 21.79920 3.173114 75.02768 0.000000 0.000000 0.000000
30 31.21845 4.910377 61.72163 1.784894 0.001183 0.36346690 31.42500 5.438533 60.84827 1.925888 0.001301 0.361007
Period ATX WIG PX BUX BET SOFIX1 16.21773 4.740944 7.948067 71.09326 0.000000 0.000000
30 29.01829 6.690134 13.64212 50.32515 0.205289 0.11902190 29.81494 7.025592 13.85145 48.98721 0.207251 0.113559
Period ATX WIG PX BUX BET SOFIX1 0.045655 0.001999 0.025464 0.005082 99.92180 0.000000
30 0.236730 0.805854 0.233885 2.838162 95.52907 0.35630490 0.245924 1.730081 0.250796 3130038 94.27640 0.366764
Period ATX WIG PX BUX BET SOFIX1 0.097580 0.002854 0.013009 0.029495 0.009514 99.84755
30 0.131636 4.089252 0.035681 0.856636 0.048411 94.8383890 0.348825 8.306711 0.034418 1.198519 0.048603 90.06292
Variance Decomposition of BET volatility
Variance Decomposition of SOFIX volatility
Variance Decomposition of ATX volatility
Variance Decomposition of WIG volatility
Variance Decomposition of PX volatility
Variance Decomposition of BUX volatility
ConclusionsConclusions
There are no cointegration relationships between the There are no cointegration relationships between the countries under studycountries under study None of the emerging markets has a significant influence on None of the emerging markets has a significant influence on the industrialized marketthe industrialized market There are unidirectional spillovers from Austria to Poland, There are unidirectional spillovers from Austria to Poland, Hungary and the Czech Republic in term of returns and Hungary and the Czech Republic in term of returns and volatility. volatility. Between the larger emerging markets there are correlationsBetween the larger emerging markets there are correlationsrelationships in returns and volatilityrelationships in returns and volatility. . Romania and Bulgarian stock markets are driven mainly by Romania and Bulgarian stock markets are driven mainly by the developments at domestic levelthe developments at domestic level. . Spillover effects between volatilities are stronger compared Spillover effects between volatilities are stronger compared to spillover effects between returns. to spillover effects between returns.
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Coefficient Std. Error t-Statistic Prob. C(1) 0.160751 0.005633 28.53943 0.0000C(2) 0.056116 0.004273 13.13232 0.0000C(3) -0.033904 0.043034 -0.787851 0.4309C(4) 0.233037 0.080167 2.906890 0.0037C(5) 0.369370 0.012866 28.70958 0.0000
R-squared 0.988895 2173.383Adjusted R-squared 0.988864 1150.403S.E. of regression 121.3962 12.43941Sum squared resid 21471850 12.45749Log likelihood -9088.209 0.045170 Durbin-Watson stat
ATX=C(1)*BET+C(2)*BUX+C(3)*SOFIX+C(4)*PX+C(5)*WIGIncluded observations: 1462 after adjusting endpoints
Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion
Sample(adjusted): 10/20/2000 5/29/2006Date: 06/20/07 Time: 02:42Method: Least SquaresDependent Variable: ATX Dependent Variable: BET
Method: Least SquaresDate: 06/20/07 Time: 02:38Sample(adjusted): 10/20/2000 5/29/2006Included observations: 1462 after adjusting endpointsBET=C(1)*ATX+C(2)*BUX+C(3)*SOFIX+C(4)*PX+C(5)*WIG
Coefficient Std. Error t-Statistic Prob.
C(1) 2.230612 0.078159 28.53943 0.0000C(2) -0.036820 0.016806 -2.190921 0.0286C(3) 2.854737 0.141828 20.12813 0.0000C(4) 0.603770 0.299075 2.018791 0.0437C(5) -1.450192 0.046399 -31.25499 0.0000R-squared 0.973051 Mean dependent var 3540.710Adjusted R-squared 0.972977 S.D. dependent var 2750.874S.E. of regression 452.2098 Akaike info criterion 15.06958Sum squared resid 2.98E+08 Schwarz criterion 15.08767Log likelihood -11010.87 Durbin-Watson stat 0.037582
Dependent Variable: BUXMethod: Least SquaresDate: 06/20/07 Time: 02:43Sample(adjusted): 10/20/2000 5/29/2006Included observations: 1462 after adjusting endpointsBUX=C(1)*ATX+C(2)*BET+C(3)*SOFIX+C(4)*PX+C(5)*WIG
Coefficient Std. Error t-Statistic Prob. C(1) 1.886040 0.143618 13.13232 0.0000C(2) -0.089182 0.040705 -2.190921 0.0286C(3) -3.807791 0.228730 -16.64756 0.0000C(4) 13.40919 0.306340 43.77223 0.0000C(5) -0.159655 0.093236 -1.712374 0.0870R-squared 0.987852 Mean dependent var 13089.12Adjusted R-squared 0.987819 S.D. dependent var 6376.682S.E. of regression 703.7783 Akaike info criterion 15.95422Sum squared resid 7.22E+08 Schwarz criterion 15.97230Log likelihood -11657.53 Durbin-Watson stat 0.065961
Dependent Variable: PXMethod: Least SquaresDate: 07/09/07 Time: 03:45Sample(adjusted): 10/20/2000 5/29/2006Included observations: 1462 after adjusting endpointsPX=C(1)*ATX+C(2)*BET+C(3)*BUX+C(4)*SOFIX+C(5)*WIG
Coefficient Std. Error t-Statistic Prob. C(1) 0.024744 0.008512 2.906890 0.0037C(2) 0.004620 0.002288 2.018791 0.0437C(3) 0.042362 0.000968 43.77223 0.0000C(4) 0.289009 0.011806 24.47900 0.0000C(5) 0.045756 0.005107 8.959594 0.0000R-squared 0.991982 Mean dependent var 856.4309Adjusted R-squared 0.991960 S.D. dependent var 441.1593S.E. of regression 39.55700 Akaike info criterion 10.19678Sum squared resid 2279850. Schwarz criterion 10.21486Log likelihood -7448.844 Durbin-Watson stat 0.059943
Engle Granger residual base cointegration testEngle Granger residual base cointegration test
Dependent Variable: SOFIXMethod: Least SquaresDate: 06/20/07 Time: 02:45Sample(adjusted): 10/20/2000 5/29/2006Included observations: 1462 after adjusting endpointsSOFIX=C(1)*ATX+C(2)*BET+C(3)*BUX+C(4)*PX+C(5)*WIG
Coefficient Std. Error t-Statistic Prob. C(1) -0.012560 0.015942 -0.787851 0.4309C(2) 0.076213 0.003786 20.12813 0.0000C(3) -0.041970 0.002521 -16.64756 0.0000C(4) 1.008339 0.041192 24.47900 0.0000C(5) -0.030242 0.009766 -3.096585 0.0020R-squared 0.959420 Mean dependent var 497.5816Adjusted R-squared 0.959309 S.D. dependent var 366.2858S.E. of regression 73.88751 Akaike info criterion 11.44638Sum squared resid 7954294 Schwarz criterion 11.46446Log likelihood -8362.303 Durbin-Watson stat 0.029330
Dependent Variable: WIGMethod: Least SquaresDate: 06/20/07 Time: 02:49Sample(adjusted): 10/20/2000 5/29/2006Included observations: 1462 after adjusting endpointsWIG=C(1)*ATX+C(2)*BET+C(3)*BUX+C(4)*SOFIX+C(5)*PX
Coefficient Std. Error t-Statistic Prob. C(1) 0.978186 0.034072 28.70958 0.0000C(2) -0.276768 0.008855 -31.25499 0.0000C(3) -0.012580 0.007347 -1.712374 0.0870C(4) -0.216194 0.069817 -3.096585 0.0020C(5) 1.141233 0.127376 8.959594 0.0000R-squared 0.920975 Mean dependent var 1872.073Adjusted R-squared 0.920758 S.D. dependent var 701.7897S.E. of regression 197.5536 Akaike info criterion 13.41331Sum squared resid 56862958 Schwarz criterion 13.43139Log likelihood -9800.130 Durbin-Watson stat 0.034693
Engle Granger residual base cointegration testEngle Granger residual base cointegration test
Dependent Variable: D_ATXMethod: ML - ARCH (Marquardt)Date: 06/20/07 Time: 03:07Sample(adjusted): 10/23/2000 5/29/2006Included observations: 1461 after adjusting endpointsConvergence achieved after 17 iterationsVariance backcast: ON
Coefficient Std. Error z-Statistic Prob. C 0.001524 0.000226 6.734204 0.0000
C 1.29E-05 2.00E-06 6.481563 0.0000ARCH(1) 0.125142 0.018366 6.813744 0.0000
GARCH(1) 0.765879 0.030141 25.40960 0.0000R-squared -0.002485 Mean dependent var 0.000999Adjusted R-squared -0.004549 S.D. dependent var 0.010543S.E. of regression 0.010567 Akaike info criterion -6.351087Sum squared resid 0.162692 Schwarz criterion -6.336612
Variance Equation Variance Equation
Dependent Variable: D_BUXMethod: ML - ARCH (Marquardt)Date: 06/20/07 Time: 03:11Sample(adjusted): 10/23/2000 5/29/2006Included observations: 1461 after adjusting endpointsConvergence achieved after 9 iterationsVariance backcast: ON
Coefficient Std. Error z-Statistic Prob. C 0.001038 0.000357 2.908883 0.0036
C 9.80E-06 2.83E-06 3.465744 0.0005ARCH(1) 0.070711 0.013044 5.420837 0.0000
GARCH(1) 0.881748 0.022236 39.65325 0.0000R-squared -0.000434 Mean dependent var 0.000739Adjusted R-squared -0.002494 S.D. dependent var 0.014391S.E. of regression 0.014409 Akaike info criterion -5.704374Sum squared resid 0.302492 Schwarz criterion -5.689899Log likelihood 4171.045 Durbin-Watson stat 1.945470
Variance Equation
Dependent Variable: D_BETMethod: ML - ARCH (Marquardt)Date: 06/20/07 Time: 03:09Sample(adjusted): 10/23/2000 5/29/2006Included observations: 1461 after adjusting endpointsConvergence achieved after 13 iterationsVariance backcast: ON
Coefficient Std. Error z-Statistic Prob. C 0.001599 0.000305 5.247555 0.0000
C 1.09E-05 1.69E-06 6.428384 0.0000ARCH(1) 0.202481 0.021477 9.428005 0.0000
GARCH(1) 0.760199 0.021575 35.23453 0.0000R-squared -0.000293 Mean dependent var 0.001845Adjusted R-squared -0.002352 S.D. dependent var 0.014388S.E. of regression 0.014405 Akaike info criterion -5.866433Sum squared resid 0.302325 Schwarz criterion -5.851958Log likelihood 4289.429 Durbin-Watson stat 1.639734
Variance Equation
Dependent Variable: D_PXMethod: ML - ARCH (Marquardt)Date: 06/20/07 Time: 03:15Sample(adjusted): 10/23/2000 5/29/2006Included observations: 1461 after adjusting endpointsConvergence achieved after 18 iterationsVariance backcast: ON
Coefficient Std. Error z-Statistic Prob. C 0.001361 0.000290 4.698530 0.0000
C 1.35E-05 2.83E-06 4.776848 0.0000ARCH(1) 0.113726 0.017111 6.646257 0.0000
GARCH(1) 0.811543 0.030036 27.01892 0.0000R-squared -0.001571 Mean dependent var 0.000837Adjusted R-squared -0.003633 S.D. dependent var 0.013201S.E. of regression 0.013225 Akaike info criterion -5.914921Sum squared resid 0.254829 Schwarz criterion -5.900447Log likelihood 4324.850 Durbin-Watson stat 1.892869
Variance Equation
Estimating the volatilitiesEstimating the volatilities
Dependent Variable: D_SOFIXMethod: ML - ARCH (Marquardt)Date: 06/20/07 Time: 03:13Sample(adjusted): 10/23/2000 5/29/2006Included observations: 1461 after adjusting endpointsConvergence achieved after 41 iterationsVariance backcast: ON
Coefficient Std. Error z-Statistic Prob. C 0.001427 0.000254 5.619383 0.0000
C 6.03E-07 1.34E-07 4.511134 0.0000ARCH(1) 0.106533 0.006070 17.55001 0.0000
GARCH(1) 0.908129 0.003494 259.9401 0.0000R-squared -0.000280 Mean dependent var 0.001750Adjusted R-squared -0.002339 S.D. dependent var 0.019305S.E. of regression 0.019327 Akaike info criterion -5.723838Sum squared resid 0.544256 Schwarz criterion -5.709364Log likelihood 4185.264 Durbin-Watson stat 2.129854
Variance Equation
Dependent Variable: D_WIGMethod: ML - ARCH (Marquardt)Date: 06/20/07 Time: 03:16Sample(adjusted): 10/23/2000 5/29/2006Included observations: 1461 after adjusting endpointsConvergence achieved after 12 iterationsVariance backcast: ON
Coefficient Std. Error z-Statistic Prob. C 0.000860 0.000381 2.258107 0.0239
C 2.56E-06 1.02E-06 2.525784 0.0115ARCH(1) 0.036995 0.007936 4.661851 0.0000
GARCH(1) 0.952114 0.010197 93.36855 0.0000R-squared -0.000454 Mean dependent var 0.000527Adjusted R-squared -0.002514 S.D. dependent var 0.015605S.E. of regression 0.015624 Akaike info criterion -5.543496Sum squared resid 0.355682 Schwarz criterion -5.529021Log likelihood 4053.524 Durbin-Watson stat 1.883032
Variance Equation
Estimating the volatilitiesEstimating the volatilities
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